Part 2 Successfully Applying Laboratory Systems to Your Organization's Work
And thank you for the introduction, and welcome. To the second session in this series. As. We've, noted in the first session this, companion, book will provide useful background information, on, the. Technologies. And support. And other factors, that ink, can, impact your ability to effectively, use laboratory. Informatics systems. For. Many people myself included, when. We hear the phrase return. On investment, we. Think in terms of financial issues or investing, in something that will turn a profit. Aside. From commercial. Testing laboratories. Laboratories. And organizations. Are usually cost centers not, income producing so. What, exactly does, rry mean in that kind of a setting. When we look for an answer to that question we. Also have to ask why, do we invest in laboratory, informatics and automation systems. We. Do it because, there's a need that can't, be met and otherwise that tends. To boil down to words, and phrases like productivity. Efficiency. And. Improving. Lab operations. Basically. To, give us tools to help us get our work done better and at, lower cost. How. Do we structure that investment, and what should we expect as, a result, and finally. How do we evaluate the alternatives. Well. We usually think in terms of return on investment, we, need to consider the results of that investment, because. Once those investments, have been made the. Nature of laboratory, work will change the. Return on those investments is, demonstrated. By what they enable us to do. We. Will be spending this session on our wine but. What we will. Be covering all the details, the. Rest additional, comments, about, that subject will occur throughout the webinar series as we. Look at issues about the impact of technologies. On lab performance, and the, costs, and benefits associated. With them. Because. Most of the people will be discussing, funding, with will. Think in terms of return on investment, investment. Will, stick with that terminology, but. Keep considerations. About the results, of investing, in the, forefront of your thinking. All. Our Y considerations. Can come up in different ways, one. Is when you're evaluating alternative. Approaches, to handling a project, giving. Choices which. Is the most cost effective and has, the highest likelihood of success. Maximizing. Or at least ensuring, a good return on investment. Takes preparation. We'll. Look at that preparation, and how it can be used to gain and justify, funding. Another. Is when. You have to actually just. Finding. Group, many. Of the people in that group may. Not understand, much about lab work but. They do understand, money in budgets, if. They fund your requests, they, may not be able to fund other work. You. Have to make your case in terms that they will understand. You'll. Also have to convince them that your, program is sound from both of fiscal, and lab, operations, management, perspective. We. Need to define what we mean by the word investment. Investments. Will consist, of people and their time, funding. For equipment systems. And planning. Some. Of the people you will need access to will be from your group as well as other organizations, IT. Support, for example, some. May be resources, you don't currently have. People's. Time will have to be funded and justified, particularly. If there are other projects, competing, for their attention. Having. People understand. The. Nature of the return may be a challenge, again, particularly, if lab work isn't familiar to them. It's. Not as simple to understand, the stock market investing, for example where. You invest funds and you expect to return to the same kind. Given. The subject we were discussing the return will be funds returned, on monetary, investment, they, will be in terms of improving lab operations, and performance as, you.
Will See shortly you. Have to define what that means for your organization. In. Order to achieve your investment, goals and laboratory, work you. May find that you'll be breaking new ground in your company such. As automation, of methods, dealing. With new technologies. Making. Changes, to lab operations, which. Includes people taking, on new roles such. As project management. These. Are not reasons, to avoid the work but. To go in with your eyes open and consider. New ways of working. John. Trig formerly. A phase for informatics, gave. The following comments, in a presentation, he gave a few years ago. Defining. Our wine is one of the big challenges of project, phases it's. Often based on faith not data there's. An issue of trust that the decisions, are well-founded, and researched, and that, the direction you're going makes, sense both technically, and in, terms of resource utilization. Time. Savings, are soft dollars, they. Have to be turned into productive, use if. You free. Up people's time what. Are they going to do with it and will. They need more education to, get that work done. Often. The, investment, required is significant, so. The organization. They have to take a big risk, large. Companies, may have their own formal. Or online, process. Those. Funding, projects, will be concerned about the costs, and whether or not the project has been well thought through, they'll. Be looking at the benefits, that we'll get from their investment, and everything. Comes down to a very simple question what's. The return on the investment. They. May have concerns, about the likelihood of success of the project. Lab. Information technology. Projects, have a reputation, sometimes. Deserved, for. Cost overruns, and schedule issues, how. Is your project going to be different. How. Do you go about answering that we. Need to look at some points that will help you respond, and lay, out a realistic, approach to deciding, what investments, to make when. To make them and then how, to justify your programs. How. Do you go about preparing, for funding and project approval. Requests, let's. Assume you're talking to people who don't understand, lab work. First. You. Need to set a clear statement of goals for laboratory, work, to. You the goals may seem obvious to. Those outside, the lab those, reviewing, your proposals, they may not be. Having. Clearly, stated goals that they can buy into and use as a reference point for technology, programs, and projects, will. Make your life a lot easier. You. Need to have people understand, what your lab does and how it affects other parts of the organization. One. Thing that will help is to put together the story that helps them understand, how a lab transitions. From. One relying, on human, effort to. One using current informatics, nation technologies. Laboratories. Really start with a high level of assistance technologies. They. Grow into them as needs, develop. One. Of the returns on investment, is the development, of an overall plan and, technology. Infrastructure, that. Forms a basis for further maturation. Finally. They. Would like to know why are you making these investments, what's. Changed, that makes those investments, important, now. We're. Going to list, potential gold now and then. Look at look. At how technologies. And planning can impact them, there. Are goals that your lab has for the scientific mission they. May speak to the nature of the research you're doing or. House of QC lab is going to support a production process, the. Goal. Is referenced, here are those. That pertain to the use of informatics, and automation technologies. Within. Those environments. It. Will be useful as part. Of both a projects justification. And evaluation. To. See how what you do affects these goals and these. Are the goals I'm suggesting to. Produce. Results, knowledge. Information. And data that are, of high quality and, integrity. Optimizing. Productivity. And ROI. And, putting. The results, of laboratory work in, an, environment, that fosters a high rate of utilization, and availability. Basically. Effective, knowledge and intellectual. Property management. These. Are broad statements, in part because there are many different types of laboratories, and scientific, groups doing. Different things some. Work is done in a bench setting and some in the field and some. Such as space sciences, and astronomy, use, really expensive tools for data gathering in. The, next few slides we'll. Address those goals individually. Producing. Knowledge information. And data that is of high quality integrity. Might. Seem obvious but it's, a really hot topic in, some fields, particularly, life sciences, but, that also extends, the fields such as economics. Basically. You want people to know that the job of your lab is. To produce meaningful.
Results. That they can trust and will, form a found a sound basis, for. Decision, making. There's. A statement in a scientific, novel by it should be a science nonfiction novel by. Christopher, Cantrell, that. Reads the, only thing worse than no data is, data you can't trust, your. Lab and those, that use the results you produced have. To have confidence is reliability. Another. Goal is putting the results, work in an environment that fosters a high rate of utilization and, availability. This. Impacts, knowledge, and intellectual property management. We. Should be careful that data and information are organized, in ways and formats, that, can be searched archived, found, and easy to use, if. The data is in a media that is hard to work with the paper notebook, for example it won't, be used and you. Won't get the return on investment that that work could otherwise produce. Knowledge. And intellectual property management has become an important, factor in corporate, and organizational. Life, the. Payback the return is. Making, the results of lab work more accessible and useful. When. You are making a case for a program, or project you. Should look beyond the nature of the work done. In your lab and see. How it impacts other groups. Reducing. The cost per test and speeding up the testing process in quality. Control labs can. Mean faster, product releases, and give, you the ability to tackle needed, projects, that, may be pushed aside for, lack of time or people, it. Could also mean earlier detection of problems, and reducing. The amount of out of spec mature products that are being produced. If. You work and land the supports, research, how. Are those research projects, benefit from faster lower, cost analysis, and in. Research settings, what with streamline operations mean. To furthering your programs, those. Considerations, are, part of the return on investment investment. The. Use of lab technologies. Can improve the processes, that are used conduct your work. There. Is a regression for, manual to semi-automated, to fully automated, systems, in. Each case there's a cost for experiment, to consider. Manual. Work is expensive, but people are easily adaptable, to change, particularly. When methods may be updated frequently or. There's a low demand for some types of testing. Some. Stages, may be easily automated, and offload people, reducing. The cost and increasing the throughput. Fully. Automated, systems, are at least costly, to run on a per sample basis, have. A sizable, upfront cost for implementation, and one, of the least adaptable. So. What are the trade-offs in your work it, may vary from one experimental, setup to another. How. Is your data and information managed. You. May be moving from a paper-based environment. Say lab notebooks, and instrument data system printouts for example and to. An electronic, environment where labs or easily, accessed and used that. Can have a significant. Productivity, gain as well, as improved knowledge management. How. Our workflow is managed is an immanuel process based on paper records, how. Does that get done now and. What are you planning for in the future what. Problems are you having, how. About moving in two limbs for example, change, that, you'll. Get a higher level of efficiency, and may be able to reassign, someone, from clerical or, administrative, tasks, to, more productive work. How. Are the work results, reported, taking. Advantage of electronic, systems reports. Can be sent out via email, so that people will see them faster, wherever, they are if. You, were in a QC production, environment, the, test results, can be automatically, entered into a production management system, providing. Faster, data entry and better. Systems integration. How. Is the labs, knowledge. Information, and data integrated. With corporate organizational. And knowledge intellectual. Property systems, we. Touched on this earlier. Instead. Of just having a paper record you have an electronic media, based copy that. Can be integrated with other corporate intellectual. Property, including. Corporate, wide research databases. Manufacturing. Production systems. This. Would relieve, the need for manual data entry and filings, and speed. A downstream. Data analysis. Work. Excuse. Me. Some. Of the benefits for making, investments. Can. Be summarized, as follows, avoiding. New hires, improved. Data and information, quality, helping. Meet regulatory requirements. Streamlining. Lab operations. Higher. Productivity, which can be measured in more samples, per hour or, a person, faster. Research, and reducing, paperwork. Better. Information, and knowledge management. More. Effective, integration, with. Internal, and external groups. Improving. Your ability to work with lab information, and knowledge. In.
Addition, The. Effect of planning and use of informatics, and automation technologies. Will. Improve your ability to absorb future, increases in lab work and your. Ability to take on more demanding tasks, with a lower investment, that, might otherwise be required. Some. Of the investment, will be for infrastructure. Providing. A foundation for. The transition, from largely manual, operations, to. A computer controlled computer. Assisted, or, scientific. Manufacturing. And production facility. This. Is similar to other settings, where productivity, gains were found after the transition, from manual, to automated. Operations, were made, the. Extent of this investment, will depend upon the technological, maturity of, the group and the, resources, available to them, we'll. Take a look at some of these points in the next few slides. We. Use the block diagram, below. To induce, informatics, technologies, and their. Relationship, to each other. The. Diagram, on the right is, another way of showing these relationships. The. Lower light Greg box shows the operations, that occur on like the lab bench. Above. That our lab wide informatics, systems including. Office applications. And then, communications. To the rest of the organization. Including. The laboratories. Administrative. Services and production. If you're in a manufacturing, facility a. Couple. Of slides ago we use three turns computer, controlled experiments. Computer. Assisted lab work and scientific. Manufacturing. Production. We. Use this diagram to show these how they relate to each other, computer. Controlled Exploud work occurs on the lab bench where. Areas where a sample handling processing. And analysis, take place. Some. Instruments, now some investments. Can. Show a fast payback, for, example adding an autosampler to an instrument and thus. Relieving a person from having to handle sample injections. Some. Auto samplers, have sample processing capabilities. That. Can further increase productivity. However. Care has to be taken when planning for these changes, first. The new system would have to be revalidated. And any. New components, worth be qualified, for use. Second. It, would also have to be tested against the older implementation. To determine, if there, are any changes in the process of the results, these. Are just two points of concern. Robotics. For sample preparations, in another, area where gains can be made once. The engineering, for process changes is done and the, resulting system is thoroughly evaluated. This. Has been particularly, effective in life. Sciences, applications. Where. Microplates, can be used for sample handling the. Same equipment can and should be usable, in other, application, areas and industries. As, part. Of the investment, ROI, evaluation. You. Also have to determine how long the experimental, process will be in use and whether. The cost for engineering, evaluation, and equipment, is worth the effort a fully. Automated process, could be run for long periods, at the time but. Would require someone, to monitor the system and its performance. Essentially. A quality, control effort on the process. The. Fully automated system would provide better predictability for, materials, usage and offer. More consistent, and reproducible data. The. Benefits, for investments, in automation at this level, our. Productivity. That is a potential, for faster, throughput an. Option. For 24/7. Operations. For fully automated, systems. Better. Quality, data lowered. With lower variability. For duplicates, and better. Control over the process. For. Fully automated, systems, the. Ability to integrate downstream. Data entry, through. Asthma data systems for example. The. Investment, in optimizing a process, has some costs, associated with it depending. Upon the nature of the changes, aside, from the cost of the optimisation itself. When. Going from one phase of automation to another you. Have to test for an account for any variations. In the process, and their, impact, on analysis.
Results. This. Will likely require revalidation. Of the process. Automating. Sample preparation and instrument data processing, will. Get your get. Your productivity, improvements, but. Then what happens to the final results, are they. Printouts. You wind it with multiple systems, to manage this. May not meet in electrical property, and data management goals. This. Is an option an opening for improvements, in ROI in future. We'll. Come back to this when we discuss planning. The. Computer assisted lab work consists. Of software, systems that supplement. Or augment, people's ability, to work, here. We find the expected application. Of Limbs allen's office, applications. And so on, I've. Also included laboratory. Execution, systems here the. Point of laboratory, execution, systems is to help people carry out lab work but. Doesn't heavily engage with instrumentation, although. It may provide data entry capability. Limbs. And ee lens do have automated data capture, capability, but, again we'll get to that in the planning section. The. Benefits, for these investments at this level our, productivity. Again blessed. Mistreated work automatic. Reporting and processing, faster. Analysis, to results, and it. Facilitates analysis. Searching, and so on, better. Results in information, management there. Also included. If. We take the testing, and experimental. Process from, the initial sample to the final result and, create. A streamlined process that, includes sample preparation, processing. Data. Collection, and analysis and, the, results entry into a limbs or ELN you. Have an automated production operation, called scientific, manufacturing. And production. It's. A result of the optimization. Of all the tasks, and processing, that go into laboratory, work. Each. Test or experiment, has his own production line all terminal, terminating, into, the ELN, or limbs as appropriate. The. Overall logic behind it is the same as any production process, optimization, with.
A Goal of high quality products. In this case data, and information. At minimal. Cost. Is. This possible, or realistic and, the answer is yes it, does require extensive, planning, and this. Is part of the change in thinking that needs to take place in, the, nature of laboratory, work. That. Change is going on steadily as automated instruments. And tasks, have, been introduced, into lab work, we'll. Look at some of the points of concern in the next slide but, there is one thing to consider. Given. The move to integration, of inline testing and production, isn't. This the direction we're already taking. There. Are three areas we need to look at first. Of all is it technically, feasible, second. Is there. A need or justification. For a project like this and, third. Are lab. Personnel, capable, of handling these kinds of systems. Process. Analysis, is just one key point we. Need someone who's qualified for, this work who can study the process, and see. If there are any technical roadblocks, to automating, the system, those. Roadblocks can include equipment issues materials. Handling and so on. Another. Point is standardization, of equipment, unless. You have a lot of funding, and a significant. Acute need you're. Going to have to rely on commercially, available equipment, for the project. Applications. Where this can be successful, today are those, where the analysis, is based on microplate, technologies, and stant, and standardized, sample, vials, similar. To villages and auto samplers. In. Order to justify the project, you're, going to need a growing, sample processing load that, will be in place long enough with, a stable process to. Justify, the development, and equipment costs as. Part of the analysis, you should consider in an intermediate stages, of automation that. Might satisfy the need in a short term until. There is a justification. For a larger project. Part. Of those costs, will include the need to revalidate the system, and ensure. That the results produced are in, line with previous, processes. Personnel. Issues are a major consideration. Do. The people you're working with have the education, necessary to. Deal with the changing nature of their work and make, the point manage, the points on brain.
This. Would represent a significant, shift in work for manually conducted, experiments, that. Background, and that experience, would, be very useful and understanding, the automated process and. Ensuring that systems, are operating properly. One, point that needs careful consideration. Is, that of detecting, anomalies in, many. Instrument, data system combinations. The. Scientists. Or lab technician, may. Not see the actual instrument, data output, but. Rather relies, on the printed report. That. Could be a problem because the report is result of a filtered analysis, process, and may. Overlook, contaminants. Or things that just might not look right to an analyst looking at the instrument, data. If. We're going to embark on programs, like this the, automated analysis. Is going, to have to be rigorously. Designed, to. Look for problems and flag, them. If. Laboratory. Work is going to move in a direction like, this we're, going to have to spend time analyzing systems, and preparing people to work in this new environment. That. Work will start at the development, of the experimental, process if, the procedure is being considered, for what made a diplomat, a ssin in the future the. Manual, version should, be designed in a way that the transfer, from manual, to semi automated to, full fully. Automated, is, planned, for at the start. The. Procedures, documentation. Should include a list of critical points, that, need to be paid attention to. Recommendations. For equipment where. Automated, steps should be considered, and potential. Risks. If. This sounds a lot like traditional. Production manufacturing like. The production and manufacturing, products that's. Pretty much the point, those. Systems matured, to the way they are as a, result, of optimizing throughput, product, quality and cost. Those. Are the same goals with production, of laboratory, results, the. Main difference is that instead of creating things for commercial, sale you're. Using the results, of the work to, answer research questions and, support. Materials, production processes. The. Benefits, of scientific manufacturing. Operations, include, all of those of the computer-controlled, and computer insisted laboratory, work, improved. Data quality, streamlining, operations. Effective. Management of lab results, and the. Ability to integrate lab results, with other parts of the organization. Whether. Or not this is attractive, depends, on the points just covered and our, ability to answer them it.
Also Depends, on the availability, of people, to do laboratory work, if. The workload outstrip. See available human, resources this. May become a necessity in some, fields this, is already a concern. As. We've seen in this discussion the return on investment is going to be demonstrated, by the impact, to those investments, will have in, changing. And improving lab operations and, people's. Ability to work and produce results. Faster. Processing, better, quality results, and the. Ability to put those results, to water use as part. Of the organisation's, intellectual, property. Those. Improvements, in turn are going to have a beneficial, effect on the, group that needs work with them. Return. On, is a complex, issue that depends, on setting meaningful, goals. Depending. Upon the type of lab you're working in the results may be real currency but, in most cases it'll, be soft currency. Currency. That it's realized at optimizing lab operations and, its, contribution to the overall organizational. Effectiveness. If. You're looking at isolating investment, isolated, investments, to. Solve fix the bottleneck issues or looking, for limited task-oriented, purchase, your. Case may be simple to make the. Downside, of that methodology. Is, that you will find that as your needs grow particularly. If they include informatics, technologies, we've already covered you, may find yourself either either boxed, in my previous purchases, or, having to scrap earlier work and start all over again. One. Way of avoiding this is to do a lab wide plan first and then. If you purchase individual, components, make. Sure that they fit the plan so, that the pieces come together at the end. This. Chart may be difficult, to view as part of the presentation, but. It will be included with a downloadable, PDF. If. You need a larger copy give. Me a call or send me a note now send it to you. The. Key to getting a good return on investment is, planning, an education, and. Will begin to cover those points in the next session which. Is scheduled. Right now for January, 18th. 2018. So. That's pretty much the subject of our wine are. There any questions. Thank. You so much Joe for your presentation. And I'm. Gonna go ahead and open it, up for any questions, to the group that you may have regarding the. Information, that, Joe covered here or any other questions, that just might be on your mind feel, free to go ahead and type those into the chat window. While. You may take some time to go ahead and provide. Some. Of those questions in there I am going to go ahead and provide a, link, to a. Resource, that Joe has if, you are interested, in some more technical details. Of, laboratory. Technologies, so let me just go ahead and share that in the chat window with you all. Okay. And I'm gonna now include the link. There. You go okay. So. I'm not seeing any, any questions so far but maybe people are still thinking so that's perfectly fine but, Joe um can, you tell us a little bit more about how important it is for a lab data and information.
Integration With. The rest of the rest. Of the organization. Can you tell us a little bit more about that, you. Know one of the problems has come up or, actually some problem, for a long time is that. Laboratories. Of all have been viewed, is kind of a side. Issue when it comes to information, management and, technology, management. Am. I in or. Information. Technology groups. Will build, large databases, of customer database, of customers, for example or. Products, but. When, it comes to the stuff that goes on in the lab they haven't got any idea what to do with it. What, lab data. Represents. A very significant, investment in time money and it's a very valuable commodity and, as. Companies, try to bring that data into, the with. The rest of the corporate information they. Find it's really useful, and really beneficial, to get that done. The problem becomes really, acute, in research, applications. Particularly if you have multiple, labs on different. Campuses where. People may be working on similar problems the. Need to bring all that stuff together into, one spun avoids. Duplication. Of effort and, spending. Them not, spending the same money twice. Interesting. Seems like a lot to consider there, now, many of your commenting to apply to regulated, labs, what, about non-regulated. Laboratories, can you tell us a little bit more about that, well. The, regulated, versus non regulated, laboratory, is an interesting problem. You'll. Find people for example doing, discovery research, and life sciences. Who. Will look at lab work and said well we're not regulated, there's a lot of things we don't have to do. My. Perspective, is different the. Thing that you find in regulations. The guidelines, for example, the in setting, ice in ISO. 17025, as. Well as gops, and GMP s are really. Guidelines, for how laboratory, should work. How. To get laboratory, work done how, to make sure that the results, are at the high quality. Really. The difference between regulated, and Lutton and non rugged. Not. Regulated, Laboratories, is, not. So much the kind of work that's being done because, really the same work as necessary, including validation. Of. Equipment. And processes, it's. A question of who does the enforcement. In. Non-regulated. Labs the enforcement, would be done by. People in the laboratory, themselves, or in management, groups in. Regulated. Laboratories, work, is done by the agencies, that may be either. The FDA. International. Groups or so on. Submitting. A question here so we'll wait a few seconds here to see. If anything. Well. We maybe wait for any questions, are, there any other announcements, or details that you want to ask the group I know that you're continuing, to develop this, webinar series and. Maybe. You're interested in any ideas. For, future sessions. Let's. See there's, a corner oh yes. That question now came through okay so so we'll come back to that Joe, Dennis. Asks can you comment on the need for a support, structure. Or the amount of effort needed, for ongoing maintenance. Post. Implementation of, a limit system. Yeah. I'm. Having a little problem hearing you I'm not quite sure what happened something. Happened. And, like the sound having, trouble hearing things. All. Right as far as the need, for support. Post. Limbs, there. Is there on is ongoing need, for things. Such as updates. Changes. Adding, equipment. It's. A fairly significant. Effort and someone, needs to be taken has to take that fairly seriously and. It's. More than just the typical IT, people the. IT people are going to be concerned with. How. Well the computer, systems are working in the operating systems, they. May not be able to get involved very well with the actual limbs application, itself so. As things change as testing, is added these. Things need to be done very carefully they need to be documented. So. That they meet all validation, requirements and, that somebody doesn't make a change that doesn't, basically, doesn't screw something else up, I. Will, be calling we'd be talking about this to a large extent in the next session and also. In the planning sessions. So. You do need a serious support, structure, and one of the things that we've been pushing for is. A development, of a position called. Laboratory. Technology Management which. Would have the ability to bridge. The gap between laboratory. People. And. The IT structures. Okay. So that seems like it's a gateway into. A, future. Session there. Hey. I hope that answers your question Dennis, yeah, I think it does. Wonderful. Okay. So Joe, you know I don't see any other questions. You. Know we'll wait here a few more seconds to see if anything comes through of, course. But. Are there any other announcements you may want. To make to the group before we, start to close out today's, webinar.
Just, Again if you if. You liked if you have any questions, that pop up after the sessions over over. Feel. Free to send me an email my email, address. Is on the slides, if. Any if. You are. Interested in the book it's well, worth while getting and if. You are interested. There will be copies, of the slides and, the scripts, that. Will be posted in the next week or two. Okay. Absolutely, all right, well thank you Joe and thank you everyone for taking, the time to join us here today I know you all have busy schedules as, a reminder we will be sending a follow-up, to everyone, registered with. A link to the recording, as well as the slides and we'll be sending some additional, information regarding. The. Next. Webinar session, part, 3 and. If. You have any questions, feel free to go ahead and reach, out to Joe and we'll. See you next time thank you so much and have, a wonderful day.